Graphical models for multivariate Markov chains

JOURNAL OF MULTIVARIATE ANALYSIS

卷:107

Article

Colombi, R.²  Giordano, S.¹ 

[1] Univ Calabria, Dipartimento Econ & Stat, I-87036 Arcavacata Di Rende, Italy

[2] Univ Bergamo, Dipartimento Ingn Informaz & Metodi Matemat, I-24044 Dalmine Bergamo, Italy

关键词: Granger noncausality;    Conditional independence;    Generalized marginal interactions;   

DOI  :  10.1016/j.jmva.2012.01.010

来源: Elsevier

【 摘 要 】

The aim of this paper is to provide a graphical representation of the dynamic relations among the marginal processes of a first order multivariate Markov chain. We show how to read Granger-noncausal and contemporaneous independence relations off a particular type of mixed graph, when directed and bi-directed edges are missing. Insights are also provided into the Markov properties with respect to a graph that are retained under marginalization of a multivariate chain. Multivariate logistic models for transition probabilities are associated with the mixed graphs encoding the relevant independencies. Finally, an application on real data illustrates the methodology. (C) 2012 Elsevier Inc. All rights reserved.

【 授权许可】

Free